Placental measures of roundness, cord insertion centrality, volume, shape, and thickness are biomarkers of maternal-fetal growth. Deviations from expected placental morphology even as early as 11-14 weeks are related to placental dysfunction and pregnancy complications such as preeclampsia, pregnancy hypertension, gestational diabetes mellitus, and fetal chromosomal defects. The common occurrence of these deviations reveals the need for mathematical models to quantify deviations in placental morphology and assess risk of adverse pregnancy outcomes early in pregnancy. To meet this need, we have assembled a leading team of experts in placental morphology, mathematics, computer science, and obstetrics and gynecology to 1) develop and 2) validate mathematical models that predict placental dysfunction and pregnancy complications from placental morphology measurements obtained early in pregnancy. The algorithm will be developed from a large database comprised of 3D ultrasound placental images from pregnancies with known outcomes providing objective criterion in which healthy and potentially at risk patterns of placental growth can be established. A prototype for clinical software will be advanced to house the proposed models, allow for inputting of individual patient data, and generate estimates for increased risk for adverse outcomes thereby indicating patients for further investigation. The proposed models will classify individualized pregnancy risks providing a foundation for a personalized plan to manage each pregnancy.